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» Change detection based on adaptive Markov Random Fields
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ICPR
2002
IEEE
14 years 6 months ago
Face Detection and Synthesis Using Markov Random Field Models
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Sarat C. Dass, Anil K. Jain, Xiaoguang Lu
MICCAI
2007
Springer
14 years 6 months ago
Object Localization Based on Markov Random Fields and Symmetry Interest Points
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...
Branislav Micusík, Georg Langs, Horst Bisch...
CVPR
2010
IEEE
13 years 10 months ago
Facial Point Detection using Boosted Regression and Graph Models
Finding fiducial facial points in any frame of a video showing rich naturalistic facial behaviour is an unsolved problem. Yet this is a crucial step for geometric-featurebased fa...
Michel Valstar, Brais Martinez, Xavier Binefa, Maj...
3DOR
2008
13 years 7 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
TMI
1998
155views more  TMI 1998»
13 years 4 months ago
Spatio-temporal fMRI Analysis using Markov Random Fields
Abstract—Functional magnetic resonance images (fMRI’s) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activa...
Xavier Descombes, Frithjof Kruggel, D. Yves von Cr...